self-learning

name: self-learning description: "Autonomous skill generator that learns new technologies from the web. Use when, users want to learn about a new library/framework/tool, need to create a skill for an unfamiliar technology, want to research and document a technology's usage patterns, or invoke with /learn <topic>. This skill uses web search and browser tools to discover, extract, and synthesize documentation into a reusable skill."

Self-Learning Skill Generator

Autonomously research and learn new technologies from the web, then generate a reusable skill.

Usage

/learn <topic>

If <topic> is missing, show usage. If topic is ambiguous, ask to clarify:

• "react" → "React for web, React Native, or a specific library like react-query?"
• "apollo" → "Apollo GraphQL client, Apollo Server, or Apollo Federation?"
• "aws" → "Which AWS service? (S3, Lambda, DynamoDB, etc.)"

Normalize to kebab-case for filenames.

2. Discover Sources (Web Search)

Use web search tool to find authoritative documentation:

Search queries to try:

1. <topic> official documentation
2. <topic> getting started guide
3. <topic> API reference
4. <topic> GitHub repository

Source prioritization:

1. Official docs sites (e.g., docs.*, *.dev)
2. Official GitHub repositories (README, /docs)
3. Official blogs/announcements

Select 3–5 high-quality URLs maximum.

If no credible sources found, ask user to provide a URL.

3. Extract Content (URL Reading)

For each selected URL, read the content:

Extract only relevant sections:

• Installation / setup
• Core concepts
• API reference / key functions
• Common patterns / examples
• Version information

Skip irrelevant content:

• Navigation, ads, login prompts
• Unrelated sidebar content
• Comments, forums

If reading the content fails (JavaScript-heavy sites), fall back to browser agent:

Task: Navigate to <URL> and extract the main content including:
- Installation instructions
- Core concepts and API reference
- Code examples
Return the extracted content as markdown.

Record scrape timestamp for each source (use current date: YYYY-MM-DD format).

4. Generate Skill

Skills are modular, self-contained packages. Every skill consists of a required SKILL.md file and optional bundled resources:

skill-name/
├── SKILL.md (required)
│   ├── YAML frontmatter metadata (required)
│   │   ├── name: (required)
│   │   └── description: (required)
│   └── Markdown instructions (required)
└── Bundled Resources (optional)
    ├── scripts/          - Executable code (Python/Bash/etc.)
    ├── references/       - Documentation intended to be loaded into context as needed
    └── assets/           - Files used in output (templates, icons, fonts, etc.)

1. Read references/skill_creation_guide.md to understand the format and principles.
2. Synthesize the learned and extracted information into a new skill.
   • Trigger: Write a description that clearly defines when to use it.
   • Workflow: Create step-by-step instructions.
   • Format: Ensure valid YAML frontmatter and proper file structure.

5. Save the Skill

Antigravity supports two types of skills, save a global-workspace if asked.

• .agent/skills/<skill-folder>/ Workspace-specific
• ~/.gemini/antigravity/skills/<skill-folder>/ Global (all workspaces)

Create directory if it doesn't exist, warn user before overwriting existing skill.

6. Confirm to User

Report:

✓ Created skill: <topic>
  Sources scraped: <N>
  Saved to: .agent/skills/<topic>/SKILL.md
  This skill will auto-trigger when working with <topic>.

Tool Reference

• search_web: Discover documentation URLs
• read_url_content: Extract content from static pages
• browser_subagent: Extract content from JavaScript-heavy sites
• write_to_file: Save the generated skill

Critical Rules

1. Never hallucinate documentation: Only include information from scraped sources.
2. Never invent APIs: If documentation is unclear, ask the user what to do.
3. Ask for URLs: If automated discovery fails, ask user for specific URLs.
4. Verify sources: Prefer official sources over third-party tutorials.